Professor, Student Recognized for Data-Driven Research.
Professor, Student Recognized for Data-Driven Research
As Hariri Institute of Computing fellows, Prasad Patil, assistant professor of biostatistics, and Jianing Wang, a doctoral student in the Department of Biostatistics, will further their research and connect with other experts in the in the computational and data sciences field.
Prasad Patil and Jianing Wang have received fellowships from the Boston University Rafik B. Hariri Institute for Computing and Computational Science & Engineering. Patil, an assistant professor of biostatistics, has been named a Junior Faculty Fellow, and Wang, a doctoral student in the Department of Biostatistics, has been named a Graduate Student Fellow.
The Hariri Institute for Computing’s fellowships aim to both recognize outstanding, data-driven researchers and support their continued development by connecting them with one another, as well as other experts in the computational and data sciences field. The Junior Faculty Fellowship is a three-year appointment and includes a $10,000 award to further the recipient’s research, and the Graduate Student Fellowship is awarded to continuing PhD students and includes a $5,000 Academic Enhancement Award to support the student’s research experience at BU.
Patil joined the School of Public Health in 2019, and is primarily working to improve research reproducibility and replicability by developing risk prediction algorithms that incorporate data from genomics studies with the goal of generalizing data across patient cohorts and populations. He says these predictors work well when applied to cohorts of similar patients, but do not work as well when applied to cohorts in different countries or research contexts, so he is working to combine predictors from different contexts to better understand how to improve generalizability. “Improving reproducibility and replicability will ensure stronger results, and, ultimately, provide better information for clinicians when treating their patients,” Patil says.
In addition to this work, Patil is also building machine learning prediction models to address a variety of public health issues. He is working with the Department of Environmental Health to predict concentrations of air pollution around Boston Logan International Airport, as well as with the BU School of Medicine and the Massachusetts Department of Public Health to predict the risk of overdose in affected communities, specifically among those who were previously incarcerated.
Patil says he is excited to connect with and learn from other faculty members across BU throughout his fellowship. “I am still learning a lot about machine learning techniques and methods, and there are a lot of people at the Institute who are using methods that I likely don’t know about,” he says. “I am looking forward to being a part of this community and having the opportunity to be opened up to new techniques and ways of thinking.”
Wang, a second-year PhD student, says her primary work focuses on surveillance efforts for substance use disorder among Massachusetts residents. She has been working on an advanced algorithm, extended from her previously published work, to help synthesize large datasets to better understand the complex dynamics of this population, as well as estimate the population’s true size. Wang says that people with a substance use disorder are often hard to reach completely in a clinical setting and are not easily identified, so having a better understanding of these factors will help to ensure that health services and treatment are available to those who need them.
Additional aspects of Wang’s work include providing disease mapping to better understand the prevalence of substance use disorder across the Commonwealth, as well as developing an algorithm to assist other states in synthesizing and analyzing their state-level data to address this issue across the country.
Wang says that her work requires a lot of computational needs and support that she is excited to receive through her fellowship. “The Institute’s technical support and computational techniques will be extremely helpful for continuing this work,” she says. “Also, connecting with other researchers who are doing similar work but using different techniques and methods will be a great resource to help me identify the best strategies for approaching my work moving forward.”
The Hariri Institute of Computing initiates research and advances social impact initiatives at the intersection of computational and data sciences. The Institute collaborates with students, staff, and faculty from across the BU campus, as well as with industrial partners from both the private and public sectors, to transform research and promote innovation across various disciplines, including engineering, social sciences, and the arts.
Several SPH faculty members have research projects that are supported through funding from the Institute, and Elaine Nsoesie, assistant professor of global health, is currently a Junior Faculty Fellow.
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